Asset Type: Case Studies

Reducing Overage with Perceptive IRT: Minimize Monitoring Burden while Optimizing Supplies

Reducing Overage with Perceptive IRT: Minimize Monitoring Burden while Optimizing Supplies
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Situation

  • Phase III multi-center, double-blind, randomized, placebo-controlled study
  • 150 participants
  • 80+ sites across 25 countries

Challenge

The sponsor was concerned that the following factors would cause a very high level of drug wastage:

  • Large number of sites
  • Clinical supplies team did not have the capacity to closely monitor sites

 

Solution

Perceptive supply chain experts recommended Perceptive IRT’s automated supply strategy management to:

  • Ensure each site is appropriately stocked by changing the IMP supply levels to match current recruitment rate
  • Take the burden off the clinical supplies manager
  • Minimize drug wastage

What is a supply strategy?

Supply strategies determine what stock is sent to a site; they combine site needs for both:

Buffer:

  • for randomization & for unplanned needs, for example, replacing damaged stock
  • quantities based on assumptions made at the start of the trial

Prediction:

  • typically, for participants from randomization onwards
  • quantities based on participant treatment group, dosing regimen & visit schedule

Typical IRT approach

When the site is first activated, a strategy is selected based on the expected recruitment rate; this can be changed by the clinical supply manager via the IRT whenever the actual recruitment rate differs, so requires active monitoring.

Advanced IRT approach

Automated supply strategy management differs as a site’s strategy is automatically changed to align with its actual recruitment rate.

 

The automated supply strategy management process:

For this study, Perceptive IRT ensured that all participants currently in screening could be randomized (and for this design received 1 kit of active or placebo).

The stock in the initial shipment was based on a dynamic count of participants actively in screening at the site.

The stock in the resupply shipments was based on a dynamic count of participants actively in screening at the site.

The quantities to ship per strategy were defined based on assumptions at the start of the trial with the support of the study’s dedicated Perceptive IRT randomization and trial supply expert.  Clinical Supply Managers were able to amend those quantities through Perceptive IRT self-service tools, once real-world participant and site data was available.

The Perceptive IRT design also included:

  • The option for the clinical supplies team to easily override the automated supply strategy switch via our inventory management web system
  • Country-specific opt-outs for the automated process
  • Specific supply strategies for locations with a long lead time for shipments

Result:

By using Perceptive IRT to automatically optimize the supply strategy for the site’s current recruitment situation, the sponsor was able to:

  • Relieve the clinical supply manager’s burden of closely monitoring each site’s supply levels against participant recruitment
  • Avoid failed participant visits due to insufficient medication
  • Ensure that each site is on the optimum supply strategy for their current recruitment rate
  • Keep drug wastage to a minimum

More on automated supply strategy management

Automated Supply Strategy Management is one of Perceptive IRT’s advanced trial supply management options; it’s a flexible approach that can be tailored to specific protocol requirements and supply criteria.

The approach can be helpful for any type of study but is particularly useful at reducing the burden on the clinical supply manager when there are many sites.

 

Trials which benefit most

Large trials with many sites

Trials with a combination of local and central sourcing of IMP

  • The greater number of IMP types, the larger the possible combinations for resupply strategies
  • Automated switching would be used to assign a strategy based on the source settings for a site

Comparator trials where the comparator is known to be different based on participant characteristics

  • Automated switching could be used to monitor the level of comparator medication based on the number of participants with the required characteristic